بنقرة واحدة
speak
Convert text into speech with Kokoro or Noiz, including simple and timeline-aligned modes.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Convert text into speech with Kokoro or Noiz, including simple and timeline-aligned modes.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | speak |
| description | Convert text into speech with Kokoro or Noiz, including simple and timeline-aligned modes. |
Convert any text into speech audio. Supports two backends (Kokoro local, Noiz cloud), two modes (simple or timeline-accurate), and per-segment voice control.
# Kokoro (auto-detected when installed)
bash skills/speak/scripts/tts.sh speak -t "Hello world" -v af_sarah -o hello.wav
bash skills/speak/scripts/tts.sh speak -f article.txt -v zf_xiaoni --lang cmn -o out.mp3 --format mp3
# Noiz (auto-detected when NOIZ_API_KEY is set, or force with --backend noiz)
# If --voice-id is omitted, the script prints 5 available built-in voices and exits.
# Pick one from the output and re-run with --voice-id <id>.
bash skills/speak/scripts/tts.sh speak -f input.txt --voice-id voice_abc --auto-emotion --emo '{"Joy":0.5}' -o out.wav
# Noiz: optional --duration (float, seconds, range (0, 36]) for target audio length
bash skills/speak/scripts/tts.sh speak -t "Short line" --voice-id voice_abc --duration 3.5 -o out.wav
# Voice cloning (Noiz only — no voice-id needed, uses ref audio)
# Use your own reference audio: local file path or URL (only when using Noiz).
bash skills/speak/scripts/tts.sh speak -t "Hello" --ref-audio ./ref.wav -o clone.wav
bash skills/speak/scripts/tts.sh speak -t "Hello" --ref-audio https://example.com/my_voice.wav -o clone.wav
For precise per-segment timing (dubbing, subtitles, video narration).
If the user doesn't have one, generate from text:
bash skills/speak/scripts/tts.sh to-srt -i article.txt -o article.srt
bash skills/speak/scripts/tts.sh to-srt -i article.txt -o article.srt --cps 15 --gap 500
--cps = characters per second (default 4, good for Chinese; ~15 for English). The agent can also write SRT manually.
JSON file controlling default + per-segment voice settings. segments keys support single index "3" or range "5-8".
Kokoro voice map:
{
"default": { "voice": "zf_xiaoni", "lang": "cmn" },
"segments": {
"1": { "voice": "zm_yunxi" },
"5-8": { "voice": "af_sarah", "lang": "en-us", "speed": 0.9 }
}
}
Noiz voice map (adds emo, reference_audio support). reference_audio can be a local path or a URL (user’s own audio; Noiz only):
{
"default": { "voice_id": "voice_123", "target_lang": "zh" },
"segments": {
"1": { "voice_id": "voice_host", "emo": { "Joy": 0.6 } },
"2-4": { "reference_audio": "./refs/guest.wav" }
}
}
Dynamic Reference Audio Slicing:
If you are translating or dubbing a video and want each sentence to automatically use the audio from the original video at the exact same timestamp as its reference audio, use the --ref-audio-track argument instead of setting reference_audio in the map:
bash skills/speak/scripts/tts.sh render --srt input.srt --voice-map vm.json --ref-audio-track original_video.mp4 -o output.wav
See examples/ for full samples.
bash skills/speak/scripts/tts.sh render --srt input.srt --voice-map vm.json -o output.wav
bash skills/speak/scripts/tts.sh render --srt input.srt --voice-map vm.json --backend noiz --auto-emotion -o output.wav
| Need | Recommended |
|---|---|
| Just read text aloud, no fuss | Kokoro (default) |
| EPUB/PDF audiobook with chapters | Kokoro (native support) |
Voice blending ("v1:60,v2:40") | Kokoro |
| Voice cloning from reference audio | Noiz |
Emotion control (emo param) | Noiz |
| Exact server-side duration per segment | Noiz |
When the user needs emotion control + voice cloning + precise duration together, Noiz is the only backend that supports all three.
ffmpeg in PATH (timeline mode)bash skills/speak/scripts/tts.sh config --set-api-key YOUR_KEY--backend kokoro to use the local backendFor backend details and full argument reference, see reference.md.